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Datos · GitHub

Compara bases de datos, análisis, SQL y proyectos de ingeniería de datos.

Proyectos útiles de GitHub

4,974 proyectos
30estrellas
real-time_crypto_data_pipeline_using_kafka preview

I am using confluent Kafka cluster to produce and consume scraped data. In this project, I've created a real-time data pipeline that utilizes Kafka to scrape, process, and load data onto S3 in JSON format. With a producer-consumer architecture, I ensure that the data is in the right format for loading onto S3 by performing minor transformations

DatosPythonCC0-1.0GitHub

slothdb

SouravRoy-ETL

412estrellas
slothdb preview

An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.

  • SQL - 130+ features - JOINs, CTEs (recursive), window functions, QUALIFY, MERGE, subqueries, set operations
  • Live file views - CREATE LIVE VIEW caches the result and auto-refreshes on file change. Incremental CSV append path parses only new bytes on log-tail workloads

defradb

sourcenetwork

897estrellas
defradb preview

DefraDB is a Peer-to-Peer Edge-First Database. It's the core data storage system for the Source Ecosystem.

minarrow

SpaceCell

103estrellas

Fast, minimal, and ergonomic zero-copy Apache Arrow tabular data implementation in Rust, with PyO3, Python bindings, NdArray, XArray, shared-memory and low-latency SIMD for data-engineering and columnar workloads. Bridge to Polars and Arrow-rs over FFI effortlessly.

DatosRustApache-2.0GitHub

Wired

SpaceCell

44estrellas
Wired preview

Fast data transport : Apache Arrow, Protobuf and Message Pack data on the one stream. Measured faster than Arrow Flight on all open benchmarks. HTTP, TCP, QUIC, Websocket, Webtransport, Stdio, UDS, all interchangeable, with 64-byte SIMD compatibilty maintained over the network and to/from disk via custom Arrow Mmap and Parquet Readers and Writers

space-cloud

spacecloud-io

4,000estrellas
space-cloud preview

Open source Firebase + Heroku to develop, scale and secure serverless apps on Kubernetes

  • Powerful CRUD: Flexible queries, transactions, aggregations and cross-database joins
  • Realtime: Make live queries to your database
DatosGoApache-2.0GitHub

sled

spacejam

9,112estrellas
sled preview

El champán de las bases de datos integradas en fase beta

  • API similar to a threadsafe BTreeMap<[u8], [u8]>
  • serializable (ACID) transactions for atomically reading and writing to multiple keys in multiple keyspaces.
DatosRustApache-2.0GitHub

learndb-py

spandanb

1,319estrellas

Learn database internals by implementing it from scratch.

  • it has a rich sql (learndb-sql) with support for select, from, where, group by, having, limit, order by
  • custom lexer and parser built using lark

jackcess

spannm

28estrellas

A pure Java library for reading / writing Microsoft Access databases

  • Pure Java: 100% Java implementation. No native dependencies, no DLLs, no MS Access installation required.
  • Wide Version Support: Supports Access versions 2000, 2003, 2007, 2010, 2013, 2016, and 2019.
DatosJavaApache-2.0GitHub
107estrellas

Open-source pure Java JDBC driver for Microsoft Access databases (*.accdb, *.mdb). Enables client programs (e.g. OpenOffice, LibreOffice, Matlab, SQuirreL) to read and write Access databases.

  • Pure Java Power: Zero native dependencies. Runs anywhere Java 11+ is supported.
  • Drop-in Replacement: Fully compatible with previous UCanAccess versions.
DatosJavaApache-2.0GitHub

spark-notebook

spark-notebook

3,136estrellas
spark-notebook preview

Interactive and Reactive Data Science using Scala and Spark.

DatosJavaScriptApache-2.0GitHub

sparkdq

sparkdq-community

77estrellas

A lightweight, declarative PySpark framework for data quality validation — check columns, rows, and entire datasets directly in your Spark pipelines

DatosPythonApache-2.0GitHub

sparklabx

sparklabx

32estrellas
sparklabx preview

Self-hosted multi-user Apache Spark notebooks — PySpark + Scala, per-user kernel pods, MinIO IAM storage, OAuth. One Helm install. Apache-2.0.

  • Spark notebooks in the browser — PySpark, Scala (Almond), with Monaco editor, Markdown cells, kernel restart, and a Libraries dialog that wraps spark.jars.packages / import $ivy so users add Maven coordinates without editing code.
  • Embedded Spark UI + DataFlint — open the kernel's Spark Web UI (DAGs, stages, SQL plans, metrics) in-app, no port-forward. DataFlint (a Spark performance plugin) is on by default for PySpark and Scala, adding a performance tab that flags slow stages, skew, and oversized scans.
DatosTypeScriptApache-2.0GitHub

gsocanalyzer

Sparsh1212

76estrellas
gsocanalyzer preview

A blazingly fast tool to analyze all the selected organizations in Google Summer of Code in the form of graphical analytics.

DatosJavaScriptMITGitHub